Abstract
Currently, many High Efficiency Video Coding (HEVC) video steganography algorithms based on Intra Prediction Mode (IPM) have been proposed. However, the existing IPM-based steganalysis algorithms designed for H.264/AVC videos are hard to be effectively applied to HEVC. Thus, it is of significant value to study IPM-based steganalysis for HEVC videos. In this paper, the distortion process of IPM-based HEVC steganography is first modeled. We find that the basic distortion exists in the change of the relationships between each embedded IPM and the adjacent IPMs. By exploiting these characteristics, we propose a novel IPM steganalysis based on the Relationship of Adjacent IPMs (RoAIPM) feature. In detail, the designed RoAIPM feature is constructed by generating different directional Gray-Level Co-occurrence Matrices (GLCMs) and texture characteristics of three refilled matrices: MPM-IPM matrix, Left-IPM matrix and Up-IPM matrix. Experiments prove that the proposed RoAIPM feature is very sensitive to the slight change introduced by IPM-based steganography. In various coding conditions, regardless of whether the feature is after dimension reduction or not, compared with state-of-the-art works, the proposed steganalysis can both present a well higher detection accuracy against the latest IPM-based HEVC steganography methods.
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Shi, H., Sun, T., Li, Z. (2022). A HEVC Steganalysis Algorithm Based on Relationship of Adjacent Intra Prediction Modes. In: Zhao, X., Piva, A., Comesaña-Alfaro, P. (eds) Digital Forensics and Watermarking. IWDW 2021. Lecture Notes in Computer Science(), vol 13180. Springer, Cham. https://doi.org/10.1007/978-3-030-95398-0_16
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